class_docstr: Main network which does cross-lingual embeddings training
docstr: Runs whole GAN
  Arguments:
      sess(tf.session): Tensorflow Session
      local_lr(float): Learning rate
docstr_tok: ["Runs","whole","GAN","Arguments",":","sess","(","tf.session",")",":","Tensorflow","Session","local_lr","(","float",")",":","Learning","rate"]
code: def run(self, sess, local_lr):
      """
      Runs whole GAN
      Arguments:
          sess(tf.session): Tensorflow Session
          local_lr(float): Learning rate
      """
      disc_cost_acc = []
      n_words_proc = 0
      tic = time.time()
      for iters in range(0, self.iters_epoch, self.batch_size):
          # 1.Run the discriminator
          for _ in range(self.disc_runs):
              disc_result = self.run_discriminator(sess, local_lr)
              disc_cost_acc.append(disc_result[0])
          # 2.Run the Generator
          n_words_proc += self.run_generator(sess, local_lr)
          # 3.Report the metrics
          self.report_metrics(iters, n_words_proc, disc_cost_acc, tic)
  
imports: from __future__ import print_function, division
  import io
  import os
  import time
  import numpy
  import scipy
  import tensorflow
label_desc: Use image node_id 7 for calling the WordTranslator obj's underlying member method code with example usage: obj.run(sess, local_lr) without return types